Performance Optimization Strategies for Multi-Cloud Deployments in Large-Scale Organizations
Keywords:
Multi-Cloud, Performance Optimization, Cloud Deployment, Scalability, Cloud Providers, Latency, Cost Optimization, Resource Allocation, Workload Distribution, Cloud Architecture, Performance Monitoring, IT Infrastructure, Large-Scale Organizations, Cloud InteroperabilityAbstract
In today's rapidly evolving technological landscape, multi-cloud environments have become essential for large-scale organizations seeking to optimize their IT infrastructure. These environments enable businesses to leverage the strengths of various cloud providers, improving scalability, availability, and performance. However, managing performance across multiple cloud platforms poses significant challenges, including issues related to network latency, cost optimization, and interoperability. This paper explores key performance optimization strategies for multi-cloud deployments, with a focus on managing workload distribution, improving resource allocation, and ensuring seamless integration across cloud providers.
References
Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud computing—The business perspective. Decision Support Systems, 51(1), 176-189.
Nagamani, N. (2024). Multi-layer AI defense models against real-time phishing and deepfake financial fraud. ISCSITR–International Journal of Business Intelligence (ISCSITR-IJBI), 5(2), 7–21.
Iyer, B., & Henderson, J.C. (2010). Preparing for the future: Understanding the seven capabilities of cloud computing. MIS Quarterly Executive, 9(2), 117-131.
Goscinski, A., & Brock, A. (2013). Technical challenges of multi-cloud infrastructures. Cloud Computing Research and Applications, 2(1), 45-59.
Nagamani, N. (2024). AI-Driven Risk Assessment Models for Health and Life Insurance Underwriting. IACSE – International Journal of Computer Science and Engineering (IACSE-IJCSE), 5(1), 8–25. https://doi.org/10.5281/zenodo.17852768
Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., et al. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58.
Lyytinen, K., & Rose, G.M. (2003). The disruptive nature of information technology innovations. MIS Quarterly, 27(4), 557-596.
Gannon, D., & Fox, G. (2010). The impact of cloud computing on data centers. Journal of Cloud Computing, 3(2), 130-145.
Tsai, W.T., & Feng, G. (2014). Cloud computing: A new era of distributed computing. Future Generation Computer Systems, 29(1), 54-65.
McKinsey & Company (2012). The Cloud’s Impact on IT Management. McKinsey Insights.
Sheetal, J. (2024). Ensuring business continuity and high availability for SAP workloads on Microsoft Azure through cloud architecture disaster recovery and native service integration. IACSE – International Journal of Computer Technology (IACSE-IJCT), 5(1), 8–29. https://doi.org/10.5281/zenodo.17785339
Veiga, A., & Alves, F. (2013). Multi-cloud architectures and performance optimization techniques. International Journal of Cloud Computing, 6(2), 70-83.
Bernstein, A., & Miller, R. (2012). High-performance multi-cloud infrastructures. Computing, 1(2), 42-59.
Moffat, J., & Green, D. (2012). The future of cloud computing: Challenges and trends. IEEE Cloud Computing, 5(1), 44-51.
Kowalski, S. (2014). Interoperability in multi-cloud environments. Journal of Cloud Computing, 9(3), 40-51.
Xu, X., & Zhang, Z. (2011). Optimizing resource allocation in cloud environments. Future Computing and Informatics Journal, 2(4), 67-79.
Sandhu, R., & Ray, M. (2012). Security considerations in multi-cloud environments. International Journal of Network Security, 13(4), 80-92.
Liu, Y., & Liao, L. (2015). Cost optimization strategies for cloud services. Journal of Computing, 22(2), 115-124.



